A Rapid Introduction to Adaptive Filtering
In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative metho...
में बचाया:
| मुख्य लेखकों: | , |
|---|---|
| स्वरूप: | Livre numérique |
| भाषा: | Anglais |
| प्रकाशित: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2013.
Cham : Springer Nature |
| श्रृंखला: | SpringerBriefs in Electrical and Computer Engineering
|
| ऑनलाइन पहुंच: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| टिप्पणी: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • A Rapid Introduction to Adaptive Filtering, Texte imprimé, 9783642302985 • A Rapid Introduction to Adaptive Filtering, Texte imprimé, 9783642303005 |
विषय - सूची:
- Wiener Filtering and examples
- Steepest descent procedure
- Stochastic gradient adaptive filtering: LMS (Least Mean Squares), NLMS (Normalized Mean Squares)
- Sign-error algorithm, APA (Affine Projection Algorithms)
- Convergence results
- Applications
- LS (Least Squares) and RLS (Recursive Least Squares)
- Computational complexity and fast implementations
- Applications.